Abstract

Natural Language Generation (nlg) systems generate texts in English and other human languages from non-linguistic input data. Usually there are a large number of possible texts that can communicate the input data, and nlg systems must choose one of these. This decision can partially be based on style (interpreted broadly). We explore three mechanisms for incorporating style into nlg choice-making: (1) explicit stylistic parameters, (2) imitating a genre style, and (3) imitating an individual's style.